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Biorxiv : the Preprint Server for Biology
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August 12, 2024
EPInformer: a scalable deep learning framework for gene expression prediction by integrating promoter-enhancer sequences with multimodal epigenomic data
Jiecong Lin, Ruibang Luo, Luca Pinello
Gigascience
|
June 23, 2017
16GT: a fast and sensitive variant caller using a 16-genotype probabilistic model
Ruibang Luo, Michael C Schatz, Steven L Salzberg
Environmental Microbiology
|
March 26, 2021
SARS-CoV-2 biology and variants: anticipation of viral evolution and what needs to be done
Ruibang Luo, Agnès Delaunay-Moisan, Kenneth Timmis, et al.
DNA Research : an International Journal for Rapid Publication of Reports on Genes and Genomes
|
October 29, 2022
Assembly-free discovery of human novel sequences using long reads
Qiuhui Li, Bin Yan, Tak-Wah Lam, et al.
Nature Communications
|
March 15, 2026
EPInformer: scalable and integrative prediction of gene expression from promoter-enhancer sequences with multimodal epigenomic profiles
Jiecong Lin, Zhijian Li, Yajie Zhao, et al.
Nature Communications
|
March 3, 2019
A multi-task convolutional deep neural network for variant calling in single molecule sequencing
Ruibang Luo, Fritz J Sedlazeck, Tak-Wah Lam, et al.
Bioinformatics Advances
|
January 29, 2024
ClusterV-Web: a user-friendly tool for profiling HIV quasispecies and generating drug resistance reports from nanopore long-read data
Junhao Su, Shumin Li, Zhenxian Zheng, et al.
BMC Bioinformatics
|
August 3, 2023
Boosting variant-calling performance with multi-platform sequencing data using Clair3-MP
Huijing Yu, Zhenxian Zheng, Junhao Su, et al.
NAR Genomics and Bioinformatics
|
July 8, 2021
RENET2: high-performance full-text gene-disease relation extraction with iterative training data expansion
Junhao Su, Ye Wu, Hing-Fung Ting, et al.
Briefings in Bioinformatics
|
July 18, 2022
Clair3-trio: high-performance Nanopore long-read variant calling in family trios with trio-to-trio deep neural networks
Junhao Su, Zhenxian Zheng, Syed Shakeel Ahmed, et al.
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of 10
Search research articles
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Showing results (1-10 of 100) with videos related to
Sort By:
Page
of 10
Biorxiv : the Preprint Server for Biology
|
August 12, 2024
EPInformer: a scalable deep learning framework for gene expression prediction by integrating promoter-enhancer sequences with multimodal epigenomic data
Jiecong Lin, Ruibang Luo, Luca Pinello
Gigascience
|
June 23, 2017
16GT: a fast and sensitive variant caller using a 16-genotype probabilistic model
Ruibang Luo, Michael C Schatz, Steven L Salzberg
Environmental Microbiology
|
March 26, 2021
SARS-CoV-2 biology and variants: anticipation of viral evolution and what needs to be done
Ruibang Luo, Agnès Delaunay-Moisan, Kenneth Timmis, et al.
DNA Research : an International Journal for Rapid Publication of Reports on Genes and Genomes
|
October 29, 2022
Assembly-free discovery of human novel sequences using long reads
Qiuhui Li, Bin Yan, Tak-Wah Lam, et al.
Nature Communications
|
March 15, 2026
EPInformer: scalable and integrative prediction of gene expression from promoter-enhancer sequences with multimodal epigenomic profiles
Jiecong Lin, Zhijian Li, Yajie Zhao, et al.
Nature Communications
|
March 3, 2019
A multi-task convolutional deep neural network for variant calling in single molecule sequencing
Ruibang Luo, Fritz J Sedlazeck, Tak-Wah Lam, et al.
Bioinformatics Advances
|
January 29, 2024
ClusterV-Web: a user-friendly tool for profiling HIV quasispecies and generating drug resistance reports from nanopore long-read data
Junhao Su, Shumin Li, Zhenxian Zheng, et al.
BMC Bioinformatics
|
August 3, 2023
Boosting variant-calling performance with multi-platform sequencing data using Clair3-MP
Huijing Yu, Zhenxian Zheng, Junhao Su, et al.
NAR Genomics and Bioinformatics
|
July 8, 2021
RENET2: high-performance full-text gene-disease relation extraction with iterative training data expansion
Junhao Su, Ye Wu, Hing-Fung Ting, et al.
Briefings in Bioinformatics
|
July 18, 2022
Clair3-trio: high-performance Nanopore long-read variant calling in family trios with trio-to-trio deep neural networks
Junhao Su, Zhenxian Zheng, Syed Shakeel Ahmed, et al.
Page
of 10